Ratings and Reviews for Python Project: Software Engineering and Image Manipulation

Compared to the first 4 courses of this specialization, which are excellent, this one is a disaster. The organization is poor. Installation instructions are full of errata and prone to conflicts in a variety of environments. This leads to frustrated students and teaching staff, who are losing their professional tone in the forums. I get it, I also would not want to be troubleshooting massive multi-library installations for a variety of OSs for however-many-students Coursera hosts. Figuring out "what to do next" requires excessive guesswork and assumption. For instance, simply downloading and moving the lecture's .ipynb files to your local environment is only _alluded to briefly, in an optional video, without ever showing it done on screen_. The course then proceeds into an unrelated lecture. Feels very disconnected and jarring. The lectures are poor. They consist of the professor talking into the camera with no accompanying materials, and again a lack of clear direction. A concrete example: the professor talks through navigating to /usr/lib/python/site-packages/PIL/Image.py file and opening it in a text editor, all _without showing the screen or terminal_, while explicitly spelling out "See-Dee" (cd) and explaining that's how you change directories... What? There are several problems with this. 1) It is NOT an effective teaching technique to talk through such multiple dir/file traversals without showing the terminal, as it's easy to get lost from where the prof is talking about. 2) Even if there is an assumption here that the students are *SO* comfortable/advanced with *nix already that you can just talk them through that many cd's AND opening a text editor without messing up the file, WHY do you feel the need to explain what "cd" and "ls" do as if it's our first time using it? There is a strong and jarring disconnect here that makes it feel like the course was unfinished - as if the prof believed he'd have an onscreen accompaniment that never materialized. BAD. The jump in difficulty from the first 4 courses is huge, but it's largely because so many intermediary steps are ignored entirely or poorly explained. The logical composition of this course is nonsense - simple things are explained while complex things are overlooked. If by design it's _intended_ to provoke solution-searching from the student, then at least let the student know that they're expected to find the solution themselves. Overall I found this really frustrating, and a huge disappointment. Poorly thought-out, poorly executed. I imagine the people actually finishing this course are the ones who are REALLY invested in learning computer vision / these libraries for their own needs, and if you have that motivation, you can give it a try. Otherwise, I see no reason to bang your head against the wall fighting upstream against this course's shortcomings. There are plenty of other resources online for learning python and simpler projects with better documentation, that would be a more natural next step from the previous courses. Again - this does not reflect on courses 1-4 of the specialization, which are very good.

Good course

This course is not worth your time. The first four courses in this series were great. Very thorough, good instruction, an interactive textbook with code that you could experiment on, etc... The courses built on themselves and you felt like your knowledge base expanded as the course went on. This course is none of that. It has almost nothing to do with the material previously presented in the other courses. You're left to search through documentation for libraries and packages with almost no instruction. If you want to learn pillow, tesseract, or opencv, just Google them and start reading. You'll learn more that way than you will taking this course. I was finally able to complete the assignments and pass, and I'm incredibly thankful just to be done with this course, but to be honest I still feel like I don't really understand any of the aforementioned packages at all. I don't understand why this course is so bad and has so little to do with the first four courses. If it hadn't been able to take it for free, I would've felt like I'd been robbed.

I personally liked much more other courses of the specialization. There are no intermediate exercises in this one, and I find the instructor not as effective as the previous ones. All in all, it gives a good approximation of what it means to struggle with daily projects.

simply very time consuming and confusing assignments with no proper explanation about the topics.

This course was a massive jump from the previous ones. No explanatory diagrams, just narration of the contents of the Jupyter notebook.

Tasks were not interesting & material was not explained well

I would give Zero stars. This course has no links to the rest of the specialization, has no teaching, and the instructions are either inadequate or wrong. Don't waste your time or money on this last one.

The process for submitting should be fixed

The content is very very insteresting, however the way is presented is not the best. Much better the courses 1 to 4 in organization and metodology.